node { checkout scm try { docker.image('s444452/ium:1.3').inside { stage('Preparation') { properties([ parameters([ gitParameter( branchFilter: 'origin/(.*)', defaultValue: 'master', description: 'Select branch', name: 'BRANCH', type: 'PT_BRANCH' ), buildSelector( defaultSelector: upstream(), description: 'Which build to use for copying artifacts', name: 'BUILD_SELECTOR' ), string( defaultValue: "0", description: 'Build number', name: 'BUILD_NR' ), string( defaultValue: ".", description: 'Data path', name: 'DATA_PATH' ), string( defaultValue: "1", description: 'EPOCHS', name: 'EPOCHS' ), string( defaultValue: "20000", description: 'Num words', name: 'NUM_WORDS' ), string( defaultValue: "1000", description: 'Batch size', name: 'BATCH_SIZE' ), string( defaultValue: "2000", description: 'Pad length', name: 'PAD_LENGTH' ) ]) ]) } stage('Copy artifacts') { copyArtifacts filter: 'train_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset' copyArtifacts filter: 'test_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset' copyArtifacts filter: 'neural_network_evaluation.csv', projectName: "s444452-evaluation/${params.BRANCH}", optional: true copyArtifacts filter: 'model/neural_net', projectName: "s444452-training/${params.BRANCH}", selector: buildParameter('BUILD_SELECTOR') } stage('Run script') { withEnv(["BUILD_NR=${params.BUILD_NR}","DATA_PATH=${params.DATA_PATH}","EPOCHS=${params.EPOCHS}", "NUM_WORDS=${params.NUM_WORDS}", "BATCH_SIZE=${params.BATCH_SIZE}","PAD_LENGTH=${params.PAD_LENGTH}"]) { sh "python3 Scripts/evaluate_neural_network.py $BUILD_NR $DATA_PATH $EPOCHS $NUM_WORDS $BATCH_SIZE $PAD_LENGTH" } } stage('Archive artifacts') { archiveArtifacts "neural_network_evaluation.csv, evaluation.png" archiveArtifacts "my_runs/**" } } } catch (e) { currentBuild.result = "FAILED" throw e } finally { notifyBuild(currentBuild.result) } } def notifyBuild(String buildStatus = 'STARTED') { buildStatus = buildStatus ?: 'SUCCESS' def subject = "Job: ${env.JOB_NAME}" def lastline = "" try { def filePath = readFile "${WORKSPACE}/neural_network_evaluation.csv" def lines = filePath.readLines() lastline = lines.get(lines.size()-1) } catch (e) { println(e.toString()) } def details = "Build nr: ${env.BUILD_NUMBER}, status: ${buildStatus} \n url: ${env.BUILD_URL} \n build params: ${params.TEST_PARAMS} \n metrics: ${lastline}" emailext ( subject: subject, body: details, to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms' ) }